Dec 6, 2021 · We propose GaussianProductAttributes, a model to learn density-based distributed embeddings for products based on multivariate Gaussian distributions in this ...

In comparison with traditional vector representations, these density-based representations are able to model uncertainty, inclusion and entailment. We present a ...

In comparison with traditional vector representations, these density-based representations are able to model uncertainty, inclusion and entailment. We present a ...

In comparison with traditional vector representations, these density-based representations are able to model uncertainty, inclusion and entailment. We present a ...

In comparison with traditional vector representations, these density-based representations are able to model uncertainty, inclusion and entailment. We present a ...

Abstract. Multivariate Gaussian probability distributions have been used as distributed representations for text. In comparison with tra-.

In comparison with traditional vector representations, these density-based representations are able to model uncertainty, inclusion and entailment. We present a ...

GaussianProductAttributes: Density-Based Distributed Representations for Products. Hossein Ghodrati Noushahr, Jeremy Levesley, Samad Ahmadi, Evgeny Mirkes.

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GaussianProductAttributes: Density-Based Distributed Representations for Products · Author Picture Hossein Ghodrati Noushahr. University of Leicester, Leicester, ...